Open code models and ecosystems do not compete with each other
While open-source models are rapidly advancing in the field of artificial intelligence, leading labs such as Anthropic and OpenAI continue to maintain their market positions. This was reported by Zamin.uz.
According to a new theory proposed by Jessi Jang, CEO of Decagon, open-source models and the most advanced systems are not actually competitors, but rather complementary tools. This perspective helps reshape the understanding of economic balance in the tech world.
Today, many companies find it acceptable to use the most expensive and powerful models during the early stages of product development. However, once the product is ready and its tasks become clear and repetitive, entrepreneurs tend to favor switching to cheaper, open-source alternatives.
As Jessi Jang emphasizes, while expensive models are necessary for discovering new capabilities and solving complex problems, open-source models serve to deploy ready-made solutions into mass production. Data from the Vercel platform confirms this theory in practice.
In recent weeks, some open-source models have taken the lead in terms of data volume, accounting for a proportional share of all queries. Nevertheless, when viewed from the standpoint of total expenditure, the most influential labs still retain the primary share of market revenue.
According to statistics, although cheap models handle trillions of queries, the cost of a single unit of service from advanced models remains significantly higher. This indicates that major labs generate more profit with fewer queries.
The market situation is expected to shift further with the release of new models from NVIDIA. The company, leveraging its broad capabilities and technological foundation, could quickly become a leader among open-source models.
Nevertheless, leading labs currently see no cause for concern, as the scope of tasks in the AI field is expanding so rapidly that even the most complex operations demand high-level, highly intelligent models.
In summary, the AI economy is evolving into a two-layered system: advanced labs drive the discovery phase, while open-source models take responsibility for everyday production processes.
Although this system appears stable for now, as the knowledge level of knowledge level of affordable models rises, tech giants will be compelled to reassess their strategies. In the future, which direction will prevail will depend on technological efficiency and price balance.
